{"id":"W1980351757","doi":"10.1109/radar.2013.6586151","title":"eSPACE: Emergency spatial pre-SCAT for Arctic Coastal Ecosystem","year":2013,"lang":"en","type":"article","venue":"","topic":"Oil Spill Detection and Mitigation","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"GDG Environnement; Environment and Climate Change Canada","funders":"Canadian Space Agency","keywords":"Shore; Remote sensing; Geography; Spatial analysis; Baseline (sea); Digital elevation model; Arctic; Computer science; Cartography; Environmental science; Environmental resource management; Geology; Oceanography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00007202708,0.00007781904,0.00006254265,0.00001482429,0.00009543211,0.00001956561,0.00007165002,0.00004003793,0.0214206],"category_scores_gemma":[0.00002346622,0.00006557507,0.00005434774,0.00006811188,0.00001768971,0.000202924,0.00004230464,0.00003399211,0.002545345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007190581,"about_ca_system_score_gemma":0.000003176208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003395522,"about_ca_topic_score_gemma":0.01441637,"domain_scores_codex":[0.9993607,0.00001623305,0.0001446928,0.0001808506,0.0001305734,0.0001668808],"domain_scores_gemma":[0.9997261,0.00001093316,0.00004538481,0.0001183858,0.00001226986,0.0000868909],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001327076,0.0004821363,0.2530541,0.0003174559,0.00007175758,0.000001425266,0.001811181,0.002562359,0.2627081,0.001366055,0.1567595,0.3207332],"study_design_scores_gemma":[0.001519233,0.0006530192,0.7296883,0.00002370333,0.00003876035,0.00002108964,0.0006175733,0.06936757,0.05673028,0.002921994,0.1376467,0.0007717329],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.952078,0.000004108147,0.02949555,0.000509263,0.0006651243,0.0007386441,0.000007847362,0.00009232519,0.01640915],"genre_scores_gemma":[0.9788729,0.000004941935,0.0007842337,0.0000553541,0.00006434309,0.0001720578,0.000007013838,0.000009646434,0.0200295],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4766343,"threshold_uncertainty_score":0.9982313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00560119918099374,"score_gpt":0.210363863732217,"score_spread":0.2047626645512232,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}